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A panoramic view of cell population dynamics in mammalian aging.

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  • معلومة اضافية
    • المصدر:
      Publisher: American Association for the Advancement of Science Country of Publication: United States NLM ID: 0404511 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1095-9203 (Electronic) Linking ISSN: 00368075 NLM ISO Abbreviation: Science Subsets: MEDLINE
    • بيانات النشر:
      Publication: : Washington, DC : American Association for the Advancement of Science
      Original Publication: New York, N.Y. : [s.n.] 1880-
    • الموضوع:
    • نبذة مختصرة :
      To elucidate aging-associated cellular population dynamics, we present PanSci, a single-cell transcriptome atlas profiling >20 million cells from 623 mouse tissues across different life stages, sexes, and genotypes. This comprehensive dataset reveals >3000 different cellular states and >200 aging-associated cell populations. Our panoramic analysis uncovered organ-, lineage-, and sex-specific shifts in cellular dynamics during life-span progression. Moreover, we identify both systematic and organ-specific alterations in immune cell populations associated with aging. We further explored the regulatory roles of the immune system on aging and pinpointed specific age-related cell population expansions that are lymphocyte dependent. Our "cell-omics" strategy enhances comprehension of cellular aging and lays the groundwork for exploring the complex cellular regulatory networks in aging and aging-associated diseases.
    • Comments:
      Update of: bioRxiv. 2024 Mar 05:2024.03.01.583001. doi: 10.1101/2024.03.01.583001.. (PMID: 38496474)
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    • Grant Information:
      OT2 OD033760 United States OD NIH HHS; U24 HG002371 United States HG NHGRI NIH HHS; RM1 HG011014 United States HG NHGRI NIH HHS; RF1 MH132662 United States MH NIMH NIH HHS; DP2 HG012522 United States HG NHGRI NIH HHS; R01 AG076932 United States AG NIA NIH HHS
    • الموضوع:
      Date Created: 20241128 Date Completed: 20250117 Latest Revision: 20250318
    • الموضوع:
      20250318
    • الرقم المعرف:
      PMC11910726
    • الرقم المعرف:
      10.1126/science.adn3949
    • الرقم المعرف:
      39607904